Method for the absolute quantification of naturally processed HLA-restricted cancer peptides

ABSTRACT

The present invention relates to a method for the absolute quantification of naturally processed HLA-restricted cancer peptides, i.e. the determination of the copy number of peptide(s) as presented per cell. The present invention can not only be used for the development of antibody therapies or peptide vaccines, but is also highly valuable for a molecularly defined immuno-monitoring, and useful in the processes of identifying of new peptide antigens for immunotherapeutic strategies, such as respective vaccines, antibody-based therapies or adoptive T-cell transfer approaches in cancer, infectious and/or autoimmune diseases.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Non-Provisional application of U.S. ProvisionalApplication 61/097,994, filed Dec. 30, 2014, which claims priority to GB1423361.3, filed Dec. 30, 2014.

BACKGROUND Field of the Invention

The present invention relates to a method for the absolutequantification of naturally processed HLA-restricted cancer peptides,i.e. the determination of the copy number of peptide(s) as presented percell. The present invention can not only be used for the development ofantibody therapies or peptide vaccines, but is also highly valuable fora molecularly defined immuno-monitoring, and useful in the processes ofidentifying of new peptide antigens for immunotherapeutic strategies,such as respective vaccines, antibody-based therapies or adoptive T-celltransfer approaches in cancer, infectious and/or autoimmune diseases.

Description of Related Art

Development of cancer immuno-therapeutics and immuno-therapies ofautoimmune and infectious diseases aiming to induce the immune system'sT-cell arm to fight cancer might be substantially improved by a profoundknowledge of human leukocyte antigen (HLA)-bound peptide presentationlevels on primary diseased tissues. This information is relevant forantibody-based therapies or peptide vaccines in particular as well asfor any other type of T-cell vaccine based on molecular entities such asprotein, DNA or RNA. This kind of quantitative data has not beenavailable for patient-derived tissue on an absolute copy per cell-scalebefore.

A method for identifying peptides as above avoiding the “reverseimmunology”-associated problem was disclosed in EP1508047B1. Asdescribed above, this method can not be used for the quantitation ofsaid peptides. Another method employing a labeling strategy wasdisclosed in WO 2005/076009 which allowed for some quantitation, but noton an absolute scale. Other labels were disclosed, for example, in WO03/025576 or by Martin et al in Proteomics 2003, 3, 2208-2220.

Another method was disclosed by Fortier et al (The MHC class I peptiderepertoire is molded by the transcriptome, JEM, Vol. 205, No. 3, Mar.17, 2008 595-610). This method has the disadvantages that it requiresthe dissection of MHC-bound peptides from non-MHC-binding peptides dueto acid elution. This is performed using b2m-knockout cell lines: Thus,this method can not be used for primary—patient—tumor materials. In themethod, primary murine thymocytes were compared to the murine EL4 cellline. The starting amounts had been adjusted by measuring MHC Imolecules. This alone is a strong restriction of the method disclosed byFortier et al. Furthermore, a normalization as it would be required forprimary tissues of different sizes and tissue origin was not applied.Rather, balanced starting materials were used making normalizationobsolete. However, normalization is absolutely necessary for primary(patient) materials.

WO2011/128448 discloses a method for quantitatively identifying relevantHLA-bound peptide antigens from primary tissue specimens on a largescale without labeling approaches. The method comprises the steps ofproviding at least one diseased primary tissue sample and at least onesample of primary healthy tissue preferably corresponding to thediseased tissue, isolating MHC peptide ligands from said sample(s),performing an HPLC-MS analysis on said MHC ligand peptides, extractingthe precursor ion signal intensity (area) for each signal, as derivedfrom the analyses, identifying the sequences of said MHC ligandpeptides, and normalizing steps and data quality control steps in orderto relatively quantify said MHC peptide ligands without labeling.

Hassan et al. (in: Hassan C, et al, Accurate quantitation of MHC-boundpeptides by application of isotopically labeled peptide MHC complexes, JProt (2014)) disclose an approach in which isotope-labeled peptide-MHCmonomers (hpMHC) are prepared and added directly after cell lysis, i.e.before the usual sample processing. Using this approach, all lossesduring sample processing can be accounted for and allow accuratedetermination of specific MHC class I-presented ligands. The studypinpoints the immunopurification step as the origin of the ratherextreme losses during sample pretreatment and offers a solution toaccount for these losses. The strategy presented can be used to obtain areliable view of epitope copy number and thus is said to allowimprovement of vaccine design and strategies for immunotherapy.

Stimulation of an immune response is dependent upon the presence ofantigens recognized as foreign by the host immune system. The discoveryof the existence of tumor associated and disease antigens has raised thepossibility of using a host's immune system to intervene in tumorgrowth. Various mechanisms of harnessing both the humoral and cellulararms of the immune system are currently being explored for cancerimmunotherapy.

Specific elements of the cellular immune response are capable ofspecifically recognizing and destroying tumor cells. The isolation ofcytotoxic T-cells (CTL) from tumor-infiltrating cell populations or fromperipheral blood suggests that such cells play an important role innatural immune defenses against cancer. CD8-positive T-cells (T-CD8⁺) inparticular, which recognize peptides bound to class I molecules of themajor histocompatibility complex (MHC). These peptides of usually 8 to12 amino acid residues are derived from proteins or defective ribosomalproducts (DRIPS) located in the cytosol and play an important role inthis response. Human MHC-molecules are also designated as humanleukocyte-antigens (HLA).

There are two classes of MHC-molecules: MHC class I molecules that canbe found on most cells having a nucleus. MHC molecules are composed ofan alpha heavy chain and beta-2-microglobulin (MHC class I receptors) oran alpha and a beta chain (MHC class II receptors), respectively. Theirthree-dimensional conformation results in a binding groove, which isused for non-covalent interaction with peptides. MHC class I presentpeptides that result from proteolytic cleavage of predominantlyendogenous proteins, DRIPs and larger peptides. MHC class II moleculescan be found predominantly on professional antigen presenting cells(APCs), and primarily present peptides of exogenous or transmembraneproteins that are taken up by APCs during the course of endocytosis, andare subsequently processed. Complexes of peptide and MHC class Imolecules are recognized by CD8-positive cytotoxic T-lymphocytes bearingthe appropriate TCR (T-cell receptor), whereas complexes of peptide andMHC class II molecules are recognized by CD4-positive-helper-T cellsbearing the appropriate TCR. It is well known that the TCR, the peptideand the MHC are thereby present in a stoichiometric amount of 1:1:1.

For a peptide to trigger (elicit) a cellular immune response, it mustbind to an MHC-molecule. This process is dependent on the allele of theMHC-molecule and specific polymorphisms of the amino acid sequence ofthe peptide. MHC-class-I-binding peptides are usually 8-12 amino acidresidues in length and usually contain two conserved residues(“anchors”) in their sequence that interact with the correspondingbinding groove of the MHC-molecule. In this way, each MHC allele has abinding motif that controls the peptide's ability to specifically bindto the binding groove.

In the MHC class I dependent immune reaction, peptides not only have tobe able to bind to certain MHC class I molecules being expressed bytumor cells, they also have to be recognized by T cells bearing specificT cell receptors (TCR).

The antigens that are recognized by the tumor specific cytotoxic Tlymphocytes, that is, their epitopes, can be molecules derived from allprotein classes, such as enzymes, receptors, transcription factors, etc.which are expressed and, as compared to unaltered cells of the sameorigin, up-regulated in cells of the respective tumor.

The current classification of tumor associated or disease associatedantigens comprises the following major groups:

Cancer-testis antigens: The first TAAs [tumor-associated antigens;disease-associated antigens are abbreviated DAA] ever identified thatcan be recognized by T cells belong to this class, which was originallycalled cancer-testis (CT) antigens because of the expression of itsmembers in histologically different human tumors and, among normaltissues, only in spermatocytes/spermatogonia of testis and,occasionally, in placenta. Since the cells of testis do not expressclass I and II HLA molecules, these antigens cannot be recognized by Tcells in normal tissues and can therefore be considered asimmunologically tumor-specific. Well-known examples for CT antigens arethe MAGE family members or NY-ESO-1.

Differentiation antigens: These TAAs are shared between tumors and thenormal tissue from which the tumor arose; most are found in melanomasand normal melanocytes. Many of these melanocyte lineage-relatedproteins are involved in the biosynthesis of melanin and are thereforenot tumor specific but nevertheless are widely used for cancerimmunotherapy. Examples include, but are not limited to, tyrosinase andMelan-A/MART-1 for melanoma or PSA for prostate cancer.

Over-expressed TAAs: Genes encoding widely expressed TAAs have beendetected in histologically different types of tumors as well as in manynormal tissues, generally with lower expression levels. It is possiblethat many of the epitopes processed and potentially presented by normaltissues are below the threshold level for T-cell recognition, whiletheir over-expression in tumor cells can trigger an anticancer responseby breaking previously established tolerance. Prominent examples forthis class of TAAs are Her-2/neu, Survivin, Telomerase or WT1.

Tumor specific antigens: These unique TAAs arise from mutations ofnormal genes (such as β-catenin, CDK4, etc.). Some of these molecularchanges are associated with neoplastic transformation and/orprogression. Tumor specific antigens are generally able to induce strongimmune responses without bearing the risk for autoimmune reactionsagainst normal tissues. On the other hand, these TAAs are in most casesonly relevant to the exact tumor on which they were identified and areusually not shared between many individual tumors.

TAAs arising from abnormal post-translational modifications: Such TAAsmay arise from proteins which are neither specific nor over-expressed intumors but nevertheless become tumor associated by posttranslationalprocesses primarily active in tumors. Examples for this class arise fromaltered glycosylation patterns leading to novel epitopes in tumors asfor MUC1 or events like protein splicing during degradation which may ormay not be tumor specific.

Oncoviral proteins: These TAAs are viral proteins that may play acritical role in the oncogenic process and, because they are foreign(not of human origin), they can evoke a T-cell response. Examples ofsuch proteins are the human papilloma type 16 virus proteins, E6 and E7,which are expressed in cervical carcinoma.

For proteins to be recognized by cytotoxic T-lymphocytes astumor-specific or -associated antigens or disease-specific or-associated antigens, and to be used in a therapy, particularprerequisites must be fulfilled. The antigen should be expressed mainlyby tumor cells or infected cells and not at all or only in comparablysmall amounts by normal healthy tissues, for example less by the factor5, 10 or more.

In infectious diseases there are two possibilities, first the infectedcells express an antigen not expressed by healthy cells—directlyassociated to the infection—or the infected cells over-express anantigen expressed only in very small amounts by healthy cells—theover-expression of an antigen normally found in the peptidome of ahealthy cell.

It is furthermore desirable, that the respective antigen is not onlypresent in a type of tumor, infection or strain, but also in highconcentrations (i.e. copy numbers of the respective peptide per cell).Tumor-specific and tumor-associated antigens and disease-specific ordisease-associated antigens are often derived from proteins directlyinvolved in transformation of a normal cell to a tumor/infected cell dueto a function e.g. in cell cycle control or suppression of apoptosis.

In the case of cancer, additional downstream targets of the proteinsdirectly causative for a transformation may be upregulated and thus maybe indirectly tumor-associated. Such indirect tumor-associated antigensmay also be targets of a vaccination approach (Singh-Jasuja H., EmmerichN. P., Rammensee H. G., Cancer Immunol. Immunother. 2004 March; 453 (3):187-95). In both cases, it is essential that epitopes are present in theamino acid sequence of the antigen, since such a peptide (“immunogenicpeptide”) that is derived from a tumor associated or disease associatedantigen should lead to an in vitro or in vivo T-cell-response.

Basically, any peptide which is able to bind a MHC molecule may functionas a T-cell epitope. A prerequisite for the induction of an in vitro orin vivo T-cell-response is the presence of a T cell with a correspondingTCR and the absence of immunological tolerance for this particularepitope.

Therefore, TAAs and DAAs are a starting point for the development of atumor vaccine. The methods for identifying and characterizing the TAAsand DAAs are based on the use of CTL that can be isolated from patientsor healthy subjects, or they are based on the generation of differentialtranscription profiles or differential peptide expression patternsbetween tumors and normal tissues.

However, the identification of genes over-expressed in tumor tissues orhuman tumor cell lines, or selectively expressed in such tissues or celllines, does not provide precise information as to the use of theantigens being transcribed from these genes in an immune therapy. Thisis because only an individual subpopulation of epitopes of theseantigens are suitable for such an application since a T cell with acorresponding TCR has to be present and immunological tolerance for thisparticular epitope needs to be absent or minimal. It is thereforeimportant to select only those peptides from over-expressed orselectively expressed proteins that are presented in connection with MHCmolecules against which a functional T cell can be found. Such afunctional T cell is defined as a T cell which upon stimulation with aspecific antigen can be clonally expanded and is able to executeeffector functions (“effector T cell”).

T-helper cells play an important role in orchestrating the effectorfunction of CTLs in anti-tumor immunity. T-helper cell epitopes thattrigger a T-helper cell response of the T_(H1) type support effectorfunctions of CD8-positive killer T cells, which include cytotoxicfunctions directed against tumor cells displaying tumor-associatedpeptide/MHC complexes on their cell surfaces. In this waytumor-associated T-helper cell peptide epitopes, alone or in combinationwith other tumor-associated peptides, can serve as active pharmaceuticalingredients of vaccine compositions which stimulate anti-tumor immuneresponses.

Knowledge of the accurate copy number of HLA class I or II presentedligands is important in fundamental and clinical immunology. Currently,the best copy number determinations are based on mass spectrometry,employing single reaction monitoring (SRM) in combination with a knownamount of isotopically labeled peptide. Nevertheless, these approachesare still not precise enough in order to be efficiently employed in theabove approaches.

SUMMARY

In view of the above, it is therefore the object of the presentinvention to provide a method for an absolute determination of copynumbers of HLA class I or II presented ligands which is precise,efficient, easy to handle, and also can be performed on a“high-throughput” level. Other objects and advantages of the presentinvention will become readily apparent for the person of skill whenstudying the following description as provided.

In a first aspect of the present invention, the object of the inventionis solved by a method for the absolute quantification of at least oneMHC peptide ligand on a cell, said method comprising

a) preparing cells presenting said at least one MHC peptide ligand froma biological sample comprising cells,

b) determining the cell count of said preparation of step a),

c) adding a known amount of said at least one peptide-MHC ligand and/orpeptide-MHC ligandcomplex to be quantified to said preparation of stepa) (“spiking I”),

d) isolating at least one MHC peptide ligand from said preparation ofstep c) in order to obtain a peptide eluate,

e) adding a known amount of at least one MHC peptide ligand to bequantified to said peptide eluate (“spiking II”),

f) performing a mass spectrometry analysis on said at least one MHCpeptide ligand in order to generate at least one

aa) signal for the efficiency of the isolation in step d),

bb) signal for the known amount of said at least one MHC peptide ligandas added in step e), and

cc) signal for said at least one MHC peptide ligand from said preparedcells of step a),

and;

g) quantifying said at least one MHC peptide ligand based on acomparison of the signals as obtained in step f) with

aa) the cell count as obtained,

bb) the known amount of said at least one peptide-MHC ligand and/orpeptide-MHC ligand complex to be quantified as added in step c), and

cc) the known amount of at least one MHC peptide ligand to be quantifiedas added in step e),

whereby an absolute quantification of at least one MHC peptide ligand ona cell is, at least in part, achieved.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

FIGS. 1-17 depict embodiments as described herein.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT

In a method according to the present invention, where several samplesare analyzed in parallel, step c) as above can be omitted once theisolation efficiency has been established, as the efficiency for onesample can be used to estimate the isolation efficiency for a second MHCpeptide ligand and/or MHC peptide ligand complex (i.e. can be used as across-reference value).

Preferred is a method which furthermore uses the signal obtained fromthe internal calibration (spiking II) in e) as a constant and preserved(control) reference for the signal obtained from the isolated at leastone MHC peptide ligand by calculating a ratio between these two signals.This ratio is compared with the established calibration curve, whichalso includes the internal calibrant at the very same amount, preferablyby using an identical aliquot of such internal calibrant. Thecalibration curve then describes the relation between these ratios andthe amounts of peptide. See also FIG. 3 and the legend thereof.

Surprisingly, in the context of the present invention the inventorsfound that by combining the above analysis steps, for the first time,direct absolute quantitation of MHC-, preferably HLA-restricted, peptidelevels on cancer or other infected tissues in comparison to severaldifferent non-cancerous tissues or no-infected tissues and organsbecomes possible.

In the context of the present invention, “spiking” refers to theaddition of a known amount or concentration of at least one known, forexample unbound (“free”) MHC peptide ligand to be quantified to asample, such as, for example, a preparation (here designated as “spikingI”) or a peptide eluate (here designated as “spiking II”). Theamounts/concentrations of peptide(s) to be added can be readily adjustedand depend at least in part on the sample to be spiked and the methodused for the analysis.

Preferred is a method according to the present invention, wherein atleast one MHC peptide ligand is selected from a tumor associated peptide(TAA) or disease associated peptide (DAA).

Further preferred is a method according to the present invention whereinsaid biological sample comprising cells is selected from a tissuesample, a blood sample, a tumor sample, or a sample of an infectedtissue. In the context of the present invention, samples that aredirectly derived from subjects, such as patients, are termed “primary”samples, such as primary tissue or tumor samples, in contrast to samplesof cell lines, such as, for example, established tumor cell lines. Thesamples can be fresh or conserved (e.g. frozen or prepared), as long asthey are suitable for the method according to the invention. Preferredis a biological sample that does not include permanent cell lines.

As a preferred example, the HLA peptide pools from shock-frozen(primary) tissue samples can be obtained by immune precipitation fromsolid tissues using for example the HLA-A, -B, -C-specific antibodyw6/32 or the HLA-A*02-specific antibody BB7.2 coupled to CNBr-activatedsepharose, followed by acid treatment, and ultrafiltration. Fordifferent HLA-alleles other specific antibodies known in the art can beused as there are for example GAP-A3 for A*03, B1.23.2 for B-alleles.There are corresponding methods to obtain MHC-class I peptides for othermammals that are well known in the art.

The method according to the invention can also be used in the context ofinfectious diseases, such as viral or bacterial infections, for exampledengue fever, Ebola, Marburg virus, tuberculosis (TB), meningitis orsyphilis, preferable the method is used on antibiotic-resistant strainsof infectious organisms, autoimmune diseases, such as arthritis,parasitic infections, such as malaria and other diseases such as MS andMorbus Parkinson, as long as the targeted moiety is a MHC class I-boundpeptide.

Examples for autoimmune diseases (including diseases not officiallydeclared to be autoimmune diseases) are Chronic obstructive pulmonarydisease, Ankylosing Spondylitis, Crohn's Disease (one of two types ofidiopathic inflammatory bowel disease “IBD”), Dermatomyositis, Diabetesmellitus type 1, Endometriosis, Goodpasture's syndrome, Graves' disease,Guillain-Barre syndrome (GBS), Hashimoto's disease, Hidradenitissuppurativa, Kawasaki disease, IgA nephropathy, Idiopathicthrombocytopenic purpura, Interstitial cystitis, Lupus erythematosus,Mixed Connective Tissue Disease, Morphea, Myasthenia gravis, Narcolepsy,Neuromyotonia, Pemphigus vulgaris, Pernicious anemia, Psoriasis,Psoriatic Arthritis, Polymyositis, Primary biliary cirrhosis, Relapsingpolychondritis, Rheumatoid arthritis, Schizophrenia, Scleroderma,Sjogren's syndrome, Stiff person syndrome, Temporal arteritis (giantcell arteritis), Ulcerative Colitis (one of two types of idiopathicinflammatory bowel disease “IBD”), Vasculitis, Vitiligo and Wegener'sgranulomatosis.

The present invention is not restricted to human diseases, but can beused for mammals, for example cows, pigs, horses, cats, dogs, rodents,such as rat, mouse, goat, and other domestic animals.

In yet another preferred embodiment of the method according to thepresent invention, preparing of cells comprises, at least in part,enzymatic digestion of tissues, and/or cellular lysis.

Preferred is a method according to the present invention, wherein saidcell count is determined using a method selected from counting cellnuclei, photometric DNA-determination, fluorimetric DNA-determination(such as, for example, using the Qubit® technology), and quantitativePCR.

Further preferred is a method according to the present invention,further comprising determining the amount of at least one type ofHLA-molecule in said preparation of step a). Determining the amount canbe done using common methods in the art, such as methods involvingspecific antibodies e.g. in an ELISA, gels, cell sorting, and/orchromatography.

Further preferred is a method according to the present invention,wherein the at least one peptide-MHC complex as added and/or the leastone MHC peptide ligand as added are labeled, and preferably aredifferentially labeled. Respective labels are known to the person ofskill, and include isotopic labels, radioactive and non-radioactivelabels, enzymes, and other groups of preferably different masses.Preferably, the labeling is specific for specific peptides to bequantified. Most preferred is a double-labeled TAA/TUMAP, for example insituations in which two differentially labeled spikings are required inthe same experiment (see examples, below).

Preferred is a method according to the present invention, whereinisolating comprises chromatography, such as affinity chromatography.Thus, the isolated MHC/HLA ligands can be separated according to theirhydrophobicity by reversed-phase chromatography (e.g. nanoAcquity UPLCsystem, Waters) followed by detection in an ORBITRAP hybrid massspectrometer (ThermoElectron). Each sample is preferably analyzed byacquisition of replicate (e.g.) LCMS runs. The LCMS data is thenprocessed by analyzing the Tandem-MS (MS/MS) data.

The tandem-MS spectra recorded in a targeted way focusing on the m/zvalues of the peptides to be quantified are evaluated preferably by asoftware that extracts the intensities of pre-selected fragment ions ofpre-defined transitions. One example of such a software is Skyline(Maclean B et al. Skyline: an open source document editor for creatingand analyzing targeted proteomics experiments. Bioinformatics. 2010 Apr.1; 26(7):966-8), an application for analyzing mass spectrometer data ofdata independent acquisition (DIA) experiments for parallel reactionmonitoring (PRM-targeted MS/MS). This software can be used with respectto the co-eluting isotope-labeled peptide for specificity purposes aswell as in order to extract the single transition intensities forfurther processing.

Comparability of peptide groups restricted to the same HLA allelebetween different samples is possible based on a common allele-specificantibody used for purification, if available, or alternatively based onassignment of sequences to common HLA-alleles by means of anchor aminoacid patterns.

For statistic reasons, preferred is a method according to the presentinvention, wherein at least two replicate mass spectrometry runs areperformed for each at least one MHC ligand peptide.

Thus, yet another aspect of the present invention relates to a methodaccording to the present invention, further comprising selectingoverrepresented, overexpressed and/or tumor-specific MHC peptide ligandsfor the analysis.

Yet another aspect of the present invention relates to a methodaccording to the present invention, wherein said method is capable ofbeing performed or is performed on a high-throughput basis, preferablyup to 50 to 100 peptide ligands can be analyzed in parallel.

In still another preferred embodiment of the method according to thepresent invention, the steps of said method are performed in the orderas indicated in the appended claims, or as above. In still anotherpreferred method according to the present invention said method consistsof the steps as indicated above and herein.

In a further preferred aspect of the method according to the presentinvention, said method relates to personalized therapy and diagnosis.For this, said sample(s) as analyzed is/are derived from one individual,or from a group of individuals suffering from the same medical conditionas described herein. Also, a personalized MHC ligand profile, preferablya personalized quantified disease-specific MHC ligand profile, based onsaid MHC peptide ligands as quantified can be generated based on themethod according to the present invention as described herein.

Most preferably, the method according to the present invention isperformed in vitro.

In a further preferred aspect of the method according to the presentinvention, said method further comprises the step of synthesizing,preferably chemically synthesizing, said at least one MHC peptide ligandas quantified by said method on a synthesizer or manually. Anotheraspect of the invention thus relates to a method for preparing animmunoreactive peptide with which a peptide is quantified according tothe disclosed method and said peptide is synthesized chemically, invitro or in vivo. Peptides can be prepared by chemical linkage of aminoacids by the standard methods known in the art.

Peptides can be prepared in vitro, for example, in cell-free systems,and in vivo using cells. The peptides can be formulated as disclosed,for example, in EP2111867 by Lewandrowski et al.

Yet another aspect relates to the method according to the invention,wherein a further step is performed, in which the presence of theT-lymphocytes is detected. Using this method, it is possible tospecifically detect to what extent T-lymphocytes directed againstisolated and identified peptides are pre-existing in patients. Byperforming this step it is possible to apply, as a vaccine, only thosepeptides against which T-lymphocytes are already pre-existing in thepatient. The peptides can then be used to activate these specificT-lymphocytes.

A further aspect relates to the method according to the invention,wherein the detection of specific pre-existing T-lymphocytes isperformed by labeling the leukocytes with reconstituted complexes ofantigen-presenting molecules and antigenic peptide.

In yet another preferred embodiment of the method according to thepresent invention, said method does furthermore exclude the use ofknock-out cells, cell lines or animals.

A further preferred optional step of the present invention is anautomatic quality control based on molecules spiked into the samples indefined amounts.

With the method according to the invention it is furthermore possible toidentify patient-specific peptides, i.e. it is possible to preciselymatch peptides, which are to be used as vaccine, to the patient in orderto induce a specific immune response.

Another aspect of the invention then relates to a pharmaceuticalcomposition comprising defined amounts of one or more TAA and/or DAApeptides that have been quantified by the method according to theinvention.

The composition may be applied, for example, parenterally, for examplesubcutaneously, intradermally or intramuscularly, or may be administeredorally, depending on the formulation and the target disease. In doingso, the peptides are dissolved or suspended in a pharmaceuticallyacceptable carrier, preferably an aqueous carrier; the composition canfurther comprise additives, for example buffers, binders, etc. Thepeptides can also be administered together with immunostimulatingsubstances, for example cytokines.

According to one aspect of the invention, the peptides may be used forthe treatment of tumorous diseases and for preparing a drug fortreatment of tumor diseases. Tumorous diseases to be treated comprisesolid tumors, such as renal, breast, pancreas, gastric, testis and/orskin cancer or blood cancers, such as AML. This list of tumor diseasesis only exemplary, and is not intended to limit the area of application.

The peptides can further be used for assessment of the therapy-course ofa tumor disease.

The peptides can also be used for monitoring a therapy in otherimmunizations or therapies. Therefore, the peptide may not only be usedtherapeutically but also diagnostically.

A further aspect of the invention then relates to the use of thepeptides as quantified for generating an antibody. Polyclonal antibodiescan be obtained, in a general manner, by immunization of animals bymeans of injection of the peptides and subsequent purification of theimmunoglobulin. Monoclonal antibodies can be generated according tostandardized protocols known in the art.

The present invention is of particular relevance for antibody-basedapproaches, as the target's copy number on the cell surface of a targetcell determines and/or reflects, if the target is addressable for anantibody at all, and, if so, which effector functions can be used, suchas conjugated drugs, toxins, bispecific antibodies recruiting T cells orother effector cells. Other aspects relates to the use in the context ofso-called scaffolding forming molecules, such as aptamers(target-binding oligonucleic acid or peptide molecules) and/or soluble Tcell receptors (TCRs). Here again, similar as for antibodies, the copynumber determines about required avidities and effector functions. Forsaid scaffolding molecules.

Stimulation of an immune response is dependent upon the presence ofantigens recognized as foreign by the host immune system. The discoveryof the existence of tumor associated antigens has now raised thepossibility of using a host's immune system to intervene in tumorgrowth. Various mechanisms of harnessing both the humoral and cellulararms of the immune system are currently explored for cancerimmunotherapy.

Specific elements of the cellular immune response are capable ofspecifically recognizing and destroying tumor cells. The isolation ofcytotoxic T-cells (CTL) from tumor-infiltrating cell populations or fromperipheral blood suggests that such cells play an important role innatural immune defenses against cancer. CD8-positive T-cells inparticular, which recognize class I molecules of the majorhistocompatibility complex (MHC)-bearing peptides of usually 8 to 12residues derived from proteins or defect ribosomal products (DRIPS)located in the cytosols, play an important role in this response. TheMHC-molecules of the human are also designated as humanleukocyte-antigens (HLA).

MHC class I molecules can be found on most cells having a nucleus whichpresent peptides that result from proteolytic cleavage of mainlyendogenous, cytosolic or nuclear proteins, DRIPS, and larger peptides.However, peptides derived from endosomal compartments or exogenoussources are also frequently found on MHC class I molecules. Thisnon-classical way of class I presentation is referred to ascross-presentation in literature.

For proteins to be recognized by cytotoxic T-lymphocytes astumor-specific or -associated antigens, and to be used in a therapy,particular prerequisites must be fulfilled. The antigen should beexpressed mainly by tumor cells and not by normal healthy tissues or incomparably small amounts. It is furthermore desirable, that therespective antigen is not only present in a type of tumor, but also inhigh concentrations (i.e. copy numbers of the respective peptide percell). Tumor-specific and tumor-associated antigens are often derivedfrom proteins directly involved in transformation of a normal cell to atumor cell due to a function e.g. in cell cycle control or apoptosis.Additionally, also downstream targets of the proteins directly causativefor a transformation may be upregulated and thus are indirectlytumor-associated. Such indirect tumor-associated antigens may also betargets of a vaccination approach. Essential is in both cases thepresence of epitopes in the amino acid sequence of the antigen, sincesuch peptide (“immunogenic peptide”) that is derived from a tumorassociated or disease associated antigen should lead to an in vitro orin vivo T-cell-response.

Basically, any peptide able to bind a MHC molecule may function as aT-cell epitope. A prerequisite for the induction of an in vitro or invivo T-cell-response is the presence of a T cell with a correspondingTCR and the absence of immunological tolerance for this particularepitope. Therefore, TAAs are a starting point for the development of atumor vaccine. The methods for identifying and characterizing the TAAsare based on the use of CTL that can be isolated from patients orhealthy subjects, or they are based on the generation of differentialtranscription profiles or differential peptide expression patternsbetween tumors and normal tissues (Lemmel et al. 450-54; Weinschenk etal. 5818-27). However, the identification of genes over-expressed intumor tissues or human tumor cell lines, or selectively expressed insuch tissues or cell lines, does not provide precise information as tothe use of the antigens being transcribed from these genes in an immunetherapy. This is because only an individual subpopulation of epitopes ofthese antigens are suitable for such an application since a T cell witha corresponding TCR has to be present and immunological tolerance forthis particular epitope needs to be absent or minimal. It is thereforeimportant to select only those peptides from over-expressed orselectively expressed proteins that are presented in connection with MHCmolecules against which a functional T cell can be found. Such afunctional T cell is defined as a T cell that upon stimulation with aspecific antigen can be clonally expanded and is able to executeeffector functions (“effector T cell”).

Considering the severe side-effects and expenses associated withtreating cancer, better prognostic and diagnostic methods aredesperately needed.

The term “peptide” is used herein to designate a series of amino acidresidues, connected one to the other typically by peptide bonds betweenthe alpha-amino and carbonyl groups of the adjacent amino acids. Thepeptides are preferably 9 amino acids in length, but can be as short as8 amino acids in length, and as long as 10, 11, 12, 13 or 14 amino acidsin length.

The term “oligopeptide” is used herein to designate a series of aminoacid residues, connected one to the other typically by peptide bondsbetween the alpha-amino and carbonyl groups of the adjacent amino acids.The length of the oligopeptide is not critical to the invention, as longas the correct epitope or epitopes are maintained therein. Theoligopeptides are typically less than about 30 amino acid residues inlength, and greater than about 14 amino acids in length.

The term “polypeptide” designates a series of amino acid residues,connected one to the other typically by peptide bonds between thealpha-amino and carbonyl groups of the adjacent amino acids. The lengthof the polypeptide is not critical to the invention as long as thecorrect epitopes are maintained. In contrast to the terms peptide oroligopeptide, the term polypeptide is meant to refer to moleculescontaining more than about 30 amino acid residues.

A peptide, oligopeptide, protein or polynucleotide coding for such amolecule is “immunogenic” (and thus an “immunogen” within the presentinvention), if it is capable of inducing an immune response. In the caseof the present invention, immunogenicity is more specifically defined asthe ability to induce a T-cell response. Thus, an “immunogen” would be amolecule that is capable of inducing an immune response, and in the caseof the present invention, a molecule capable of inducing a T-cellresponse.

A T cell “epitope” requires a short peptide that is bound to a class IMHC receptor, forming a ternary complex (MHC class I alpha chain,beta-2-microglobulin, and peptide) that can be recognized by a T cellbearing a matching T-cell receptor binding to the MHC/peptide complexwith appropriate affinity. Peptides binding to MHC class I molecules aretypically 8-14 amino acids in length, and most typically 9 amino acidsin length.

In the present description, the invention is described using cancer asan example. Nevertheless, the inventive method can also be applied ininfectious diseases, autoimmune diseases, and parasitic infections aslong as the respective immune answer is a MHC class I involving answer.

The invention shall now be described further in the following examples,nevertheless, without being limited thereto. In the accompanying Figuresand the Sequence Listing,

FIG. 1: shows a general schematic overview over the experimentalapproach according to the present invention.

FIG. 2: shows a comparative MS analysis of a TUMAP mix with 10 fmol perTUMAP of table 1. Each peptide results in a different MS signal showingthe peptide-dependent detectability. Peptide 5 is not listed in table 1,i.e. the sequences 1-4 in table 1 correspond to Nos. 1 to 4 in FIG. 2and sequences 5-11 in table 1 correspond to Nos. 6 to 12 in FIG. 2.

Furthermore, Peptides 19, 21, and 22 in FIG. 2 are not listed in table2, i.e. the sequences 13-18 in FIG. 2 correspond to Nos. 12 to 17 intable 2, sequence 20 in FIG. 2 corresponds to No 18 in Table 2, andsequences 23 to 28 in FIG. 2 corresponds to Nos 19-24 in Table 2.

FIG. 3: shows the principle of the internal standard method. Acalibration curve is generated by titration of an isotope-labeledversion (depicted in light gray) of the TUMAP. For all MS measurements,a constant quantity of another isotope-labeled version of the TUMAPinternal standard peptide (depicted in dark gray) is spiked into the MSsamples. A calibration curve function is calculated from the ratio of MSsignals by logistic regression. The LLOQ is defined by visualexamination and considering the deviation from linearity. “Quantitationsamples” (depicted in green) represent signal intensities measured intumor samples selected for absolute quantitation of TUMAP numbers.

FIG. 4: shows calibration curves of the HLA-A*02 TUMAPs selected forabsolute quantitation. The MS results of the respective TUMAPs in tumortissue samples used for analysis of absolute TUMAP numbers per cell(“quantitation samples”) are included in each chart.

FIG. 5: shows additional calibration curves of the HLA-A*02 TUMAPsselected for absolute quantitation. The MS results of the respectiveTUMAPs in tumor tissue samples used for analysis of absolute TUMAPnumbers per cell (“quantitation samples”) are included in each chart.

FIG. 6: shows calibration curves of the HLA-A*24 TUMAPs selected forabsolute quantitation. The MS results of the respective TUMAPs in tumortissue samples used for analysis of absolute TUMAP numbers per cell(“quantitation samples”) are included in each chart

FIG. 7: shows additional calibration curves of the HLA-A*24 TUMAPsselected for absolute quantitation. The MS results of the respectiveTUMAPs in tumor tissue samples used for analysis of absolute TUMAPnumbers per cell (“quantitation samples”) are included in each chart.

FIG. 8: shows the estimated variation of MS replicate measurements overall TUMAPs analyzed. Each dot represents the coefficient of variation(CV in %) for MS replicates of an individual TUMAP in one specifictissue sample. The median of the CVs over all TUMAPs is regarded asaverage variation of MS replicate runs.

FIG. 9: shows the efficiency of the peptideMHC isolation. The efficiencyof peptideMHC isolation was determined in eight A*02-positive samplesfor A*02 TUMAPs (A), and in six A*24-positive samples for A*24 TUMAPs(B). The efficiency of isolation varies on average 24% for A*02 TUMAPsand 32% for A*24 TUMAPs, respectively (C).

FIG. 10: shows evaluation methods of DNA content analysis. A. Comparisonof three different methods for interpolation of a cell count from agiven DNA amount: using a standard curve prepared from tumor cell lines(dark gray), from PBMC of healthy donors (gray), and using thetheoretical weight of a human diploid genome (light gray). Biologicalreplicates, i.e. independent tissue lysate preparations from differentpieces of the same tumor, highlighted in grey. B. Plot of the PBMCstandard curve, which was used to determine the total cell count oftissue samples analyzed in absolute TUMAP quantitation.

FIG. 11 shows the determination of cell count from solid, frozen tissuesamples. Cell count analysis of A*02- and A*24-positive tumor samples(A) and estimated variation of cell count analysis (B). Biologicalreplicates are highlighted in grey.

FIG. 12 shows results for peptide copies per cell for HLA-A*02 TUMAPs.Eight different GC tumors were analyzed, three of them in duplicates(biological duplicates are grouped and highlighted in gray). The LLOQrefers to the quantitation range in one MS experiment and isextrapolated to a sample- and TUMAP-specific LLOQ, i.e. the lowest copynumber quantifiable in a specific sample for a specific TUMAP (depictedin gray).

FIG. 13 shows additional results for peptide copies per cell forHLA-A*02 TUMAPs. Eight different GC tumors were analyzed, three of themin duplicates (biological duplicates are grouped and highlighted ingrey). The LLOQ refers to the quantitation range in one MS experimentand is extrapolated to a sample- and TUMAP-specific LLOQ, i.e. thelowest copy number quantifiable in a specific sample for a specificTUMAP (depicted in gray).

FIG. 14 shows results for peptide copies per cell for HLA-A*24 TUMAPs.Six different GC tumors were analyzed, three of them in duplicates(biological duplicates are grouped and highlighted in grey). The LLOQrefers to the quantitation range in one MS experiment and isextrapolated to a sample- and TUMAP-specific LLOQ, i.e. the lowest copynumber quantifiable in a specific sample for a specific TUMAP (depictedin gray).

FIG. 15 shows additional results for peptide copies per cell forHLA-A*24 TUMAPs. Six different GC tumors were analyzed, three of them induplicates (biological duplicates are grouped and highlighted in grey).The LLOQ refers to the quantitation range in one MS experiment and isextrapolated to a sample- and TUMAP-specific LLOQ, i.e. the lowest copynumber quantifiable in a specific sample for a specific TU MAP (depictedin gray).

FIG. 16 shows the testing of an influence of a spiking of samples using500 fmol of free peptides in the MHC/peptide monomer preparation. Freepeptide in the analysis does not have a substantial influence for thepeptides as indicated.

FIG. 17 shows the results of tests for the DNA isolation reproducibilityusing Qubit HS (fluorescence) vs. a standard curve. The samples (cancersamples, such as NSCLC) show a sufficient homogeneity. DNA was isolatedfrom 3×50 μl aliquots.

SEQ ID No. 1 to 24 show the peptides of tables 1 and 2 that wereselected for absolute quantitation according to the examples.

EXAMPLES

The following examples describe the inventive method in the context ofTAAs/cancer. The invention is not restricted to the examples, as theyare only one preferred embodiment of the invention. For the purposes ofthe present invention, all references as cited herein are incorporatedby reference in their entireties.

TABLE 1 HLA-A*02 TUMAPs selected for absolute quantitationEleven peptides were selected for absolute quantitation. No Peptide CodeSequence  1 IGF2BP3-001 KIQEILTQV  2 FAP-003 YVYQNNIYL  3 COL12A1-002FLVDGSWSV  4 MXRA5-001 TLSSIKVEV  5 NCAPG-001 YLLSYIQSI  6 COL6A3-002FLLDGSANV  7 WNT5A-001 AMSSKFFLV  8 F2R-001 TLDPRSFLL  9 HIF1A-001ALDGFVMVL 10 MET-001 YVDPVITSI 11 CCNB1-002 ILIDWLVQV

TABLE 2 HLA-A*24 TUMAPs selected for absolute quantitation.Fourteen peptides were selected for absolutequantitation. The properties of one peptide(PLK4-001) turned out to be not suitable forfurther experiments. For the remaining 13peptides, absolute quantitation experiments were  completed. NoPeptide Code Sequence 12 ASPM-002 SYNPLWLRI 13 SLC6A6-001 VYPNWAIGL 14MMP3-001 VFIFKGNQF 15 CDC2-001 LYQILQGIVF 16 PLK4-001 QYASRFVQL 17ASPM-001 RYLWATVTI 18 ATAD2-002 KYLTVKDYL 19 KIF2C-001 IYNGKLFDLL 20MET-006 SYIDVLPEF 21 AVL9-001 FYISPVNKL 22 PPAP2C-001 AYLVYTDRL 23UCHL5-001 NYLPFIMEL 24 UQCRB-001 YYNAAGFNKL

The quantitation of TUMAP copies per cell in solid tumor samplesrequires the (sub-) quantitation of

-   -   a) the isolated TUMAP,    -   b) the loss of the TU MAP during isolation, and    -   c) the cell count of the tissue sample analyzed.

An overview on the experimental approach according to the presentinvention is given in FIG. 1.

Peptide Quantitation by NanoLC-MS/MS

For an accurate quantitation of peptides by mass spectrometry, basicknowledge about the peptide-specific correlation of peptide quantity andMS signal needs to be learned first. As an example, the MS measurementof a peptide mixture with 10 fmol per peptide reveals that there arelarge peptide-specific differences in the MS signal (FIG. 2). This alsoimplies that the range, in which a peptide may be reliably quantified byMS, depends on the individual peptide characteristics.

In addition, a linear correlation between the amount of a specificpeptide and the MS signal can only be expected within a certain range.The inventors therefore decided to determine an individual calibrationcurve for each peptide. The range of each calibration curve was selectedto reflect not only the individual quantitation range of the peptide,but also the range of MS signals for each peptide in previously analyzedtumor samples. The goal was that each calibration curve should comprisethe peptide-specific MS signal range of at least 80% of our routinesamples.

The generation of exact calibration curves requires a syntheticstandard, which has to be quantified with an independent method and hasthe same characteristics as the natural TUMAP. The inventors used doubleisotope-labeled versions of the TUMAPs, i.e. two isotope-labeled aminoacids were included during TUMAP synthesis. The double-labeled versionscan be distinguished from the natural TUMAP by a mass difference of12-18 Dalton depending on the labeled amino acid. Apart from the mass,isotope labeling does not alter the properties of the peptide in MS,i.e. peptides with the same sequence result but different isotope labelsresult in the same MS signal intensities (Anderson et al., 2012). Aftersynthesis, the double-labeled TUMAPs were precisely quantified bynitrogen analysis to allow an exact correlation of peptide quantity andMS signal.

The calibration curves were prepared in at least three differentmatrices, i.e. HLA peptide eluates from natural samples similar to theroutine MS samples, and each preparation was measured in duplicate MSruns. In order to compensate for any technical variations between MSruns, an internal standard peptide was included in all measurements. Theratio of the MS signals of the titrated peptide to the fixed internalstandard was plotted, and the calibration curve was calculated bylogistic regression (FIG. 3). The lower limit of quantitation (LLOQ) wasvisually determined considering the deviation from linearity. Ifdeviation from linearity was not obvious, such as for peptide FAP-003(FIG. 4), the mean ratio of the lowest peptide quantity was used tocalculate the LLOQ. The upper limit of quantitation, i.e. deviation fromlinearity at higher concentrations, was not reached for any calibrationcurve.

In actual quantitation experiments, the same quantity of the internalstandard was added to each sample as for the generation of thecalibration curve, and the ratio of the natural to the internal standardpeptide was calculated. This “internal standard method” is a commonmethod in MS-based protein quantitation, e.g. for biomarker analysis inbiological samples (Sturm et al., 2012; Prasad and Unadkat, 2014; Satoet al., 2012). The calibration curves and the values measured in actualtumor samples are shown in FIG. 4 and FIG. 5 for HLA-A*02 and in FIG. 6and FIG. 7 for HLA-A*24 for all TUMAPs selected for absolutequantitation.

In order to estimate the variation of quantitative MS measurements, thecoefficient of variation (CV in %) of the peptide content for each MSsample was calculated. The CVs per MS sample were plotted and theoverall variation of MS measurements was estimated as the median CV(FIG. 8).

Efficiency of Peptide/MHC Isolation

As for any protein purification process, the isolation of proteins fromtissue samples is associated with a certain loss of the protein ofinterest. To determine the efficiency of TUMAP isolation, peptideMHCcomplexes were generated for all TUMAPs selected for absolutequantitation. To be able to discriminate the spiked from the naturalpeptideMHC complexes, single-isotope-labeled versions of the TUMAPs wereused, i.e. one isotope-labeled amino acid was introduced during TUMAPsynthesis. These complexes were spiked into the freshly prepared tissuelysates, i.e. at the earliest possible point of the TUMAP isolationprocedure, and then captured like the natural peptideMHC complexes inthe following affinity purification. Measuring the recovery of thesingle-labeled TUMAPs therefore allows conclusions regarding theefficiency of isolation of individual natural TUMAPs.

The efficiency of isolation was determined in 13 samples that had beenselected for absolute TUMAP quantitation (7 HLA-A*02-positive, 5HLA-A*24-positive, and 1 HLA-A*02/A*24 double-positive sample). EightA*02-positive samples were analyzed for isolation efficiency of A*02TUMAPs and six A*24-positive samples for A*24 TUMAPs (FIG. 9 A, B). Theresults suggest that for most peptides the isolation efficiency iscomparable among different tissue samples. In contrast, the isolationefficiency differs between individual peptides. This suggests that theisolation efficiency, although determined in only a limited number oftissue samples, may be extrapolated to any other tissue preparation.However, it is necessary to analyze each TUMAP individually as theisolation efficiency may not be extrapolated from one peptide to others.

In few cases, the efficiency of isolation is unrealistically high and/orvaries strongly, e.g. for peptide NCAPG-001 (FIG. 9 A). In cases inwhich the efficiency could not be determined e.g. due topeptide-dependent difficulties with quantitation (e.g. high LLOQ levelfor peptides CCNB1-002, ASPM-001) or an efficiency higher than 100% wascalculated, the inventors assumed an isolation efficiency of 100%. Thisis a conservative approach which most likely overestimates theefficiency of isolation and thereby ultimately leads to anunderestimation of peptide copies per cell.

To estimate the variation in the efficiency of TUMAP isolation, thecoefficient of variation (CV in %) for the isolation of individualTUMAPs from 6-8 samples was plotted (FIG. 9 C). Overall, the meanvariation for A*02 TUMAPs is 24% and for A*24 TUMAPs 32%, respectively.

Determination of the Cell Count in Solid, Frozen Tissue

Another critical factor for calculating the number of peptide copies percell is the estimation of the total cell count of the tissue samplesused for TUMAP isolation. The inventors decided to use DNA contentanalysis, as this method is applicable to a wide range of samples ofdifferent origin and, most importantly, frozen samples (Forsey andChaudhuri, 2009; Alcoser et al., 2011; Alcoser et al., 2011; Silva etal., 2013).

Considering intra-tumor heterogeneity, it is necessary to determine thecell count from a tissue fraction which is representative for thecomplete tissue sample used for TUMAP isolation. The tissue lysateprepared during TUMAP isolation is a suitable sample for DNA analysis,as it is more homogenous as compared to a fraction of the solid tissue.After DNA isolation, the total DNA concentration was quantified in afluorescence-based assay (Life Technologies, Qubit HS DNA Assay), andthe total DNA content of the samples was calculated.

For the calculation of cell numbers from a given DNA quantity, theinventors considered two different methods: First, the cell number maybe calculated using the theoretical mass of a human genome, which hasbeen estimated to be approximately 6.67 pg DNA per diploid genome(Alcoser et al., 2011; Konigshoff et al., 2003). Alternatively, sampleswith known cell number may be used to prepare a DNA standard curve withthe same methods as used for the tissue samples. This method alreadycompensates for any impact of the DNA isolation and quantitationprocedure, thus improving the accuracy of our results. The inventorsprepared two different standard curves, one from seven different tumorcell lines and the other from peripheral blood mononuclear cells (PBMCs)of six different healthy donors.

To compare all three evaluation methods (theoretical DNA mass and twodifferent cell-based standard curves), the number of cells per 1 gtissue was calculated for several samples (FIG. 10 A). Calculationsusing the cell line standard result in substantially lower cell counts(max. 3.6-fold underestimation) as compared to using the PBMC standard.This was expected considering that tumor cell lines tend to have higherportions of aneuploid cells with a higher DNA content as compared tohealthy diploid PBMCs. In the literature, the proportion of diploidgastric tumors varies from 25-67% depending on the study (Hiyama et al.,1995; Tamura et al., 1991; Wiksten et al., 2008; Zhang et al., 2005;Sugai et al., 2005). As the ploidy and the fraction of aneuploid cellsof the tissue samples are unknown, both standard curves may only give anestimate on the true cell count but not consider all properties of anindividual tissue sample. Another source of variation is the unknownproliferation state of the tissue sample or the presence of necroticcells. Particularly the doubling of DNA content in proliferating cellsincreases the quantity of DNA relative to the cell number and will thusbias cell count calculation. In two normal gastric tissue samples, theinventors calculated a lower number of cells per 1 g tissue as comparedto the tumor samples with all three approaches.

As a conservative approach, the inventors decided to use the PBMCstandard curve (FIG. 10 B), which may lead to an overestimation of thecell count in the portion of hyper-diploid tissue samples, leading to anunderestimation of peptide copies per cell in such samples, but shouldnever overestimate peptide copies per cell in any sample.

For the analysis of the tissue samples selected for absolute TU MAPquantitation, the inventors isolated DNA from 2-3 aliquots of tissuelysate, and each DNA preparation was quantified in 2-3 replicates in thefluorescence-based assay. The total cell count and the cell count per 1g tissue were calculated from the total DNA content using the PBMCstandard curve (FIG. 11 A). In order to obtain an estimate of theoverall variation of cell count analysis, the coefficient of variation(%) was first determined at the level of each sample or, if available,biological replicate (i.e. independent tissue lysate preparations fromdifferent pieces of the same tumor). This calculation was taking intoaccount variation between the aliquots of tissue lysate as well asreplicate measurements in the fluorescence assay. These CVs are shown inFIG. 11 B, and the overall variation was determined as the median of thedepicted CVs. The variability may partially be explained by the factthat the tissue lysates are not entirely homogenized, i.e. remainingtissue particles containing undissociated cells result in a higher cellcount for individual isolation replicates (see e.g. GC816T in FIG. 11A).

Peptide Copies Per Cell

With data for peptide quantitation in nanoLC-MS/MS runs (“totalpeptide”), efficiency of TUMAP isolation (“% isolation efficiency”), andcell count of each tumor sample available, it is possible to calculatethe number of TUMAP copies per cell according to the following formula:

The quantity of total peptide is calculated from the result of 2-4nanoLC-MS/MS experiments (“peptide/run [fmol]”) using the calibrationcurves shown in FIG. 4 to FIG. 7.

$\begin{matrix}{{{total}\mspace{14mu}{peptide}} = {\left( {\frac{peptide}{run}\left\lbrack {f\;{mol}} \right\rbrack} \right) \times \frac{6,022 \times {10^{25}\left\lbrack \frac{1}{mol} \right\rbrack}}{10^{15}\left\lbrack \frac{f\;{mol}}{mol} \right\rbrack} \times \frac{{peptide}\mspace{14mu}{{eluate}\lbrack{\mu L}\rbrack}}{\;{{MS}{\mspace{11mu}\;}{sample}\mspace{14mu}{per}\mspace{14mu}{{run}\lbrack{\mu L}\rbrack}}} \times \frac{100\%}{\%\mspace{14mu}{of}\mspace{14mu}{lysate}\mspace{14mu}{used}\mspace{14mu}{for}\mspace{14mu}{TUMAP}\mspace{14mu}{isolation}}}} & (2)\end{matrix}$

Only MS measurements above the LLOQ, as defined using the calibrationcurves, are used for calculation of absolute peptide copy numbers. ThisLLOQ refers to the TUMAP quantity in a nanoLC-MS/MS experiment(“LLOQ/run [fmol]”).

The copy number per cell over all peptides, which could be quantified,ranges from 50 to 30000 copies per cell (see Table 3).

TABLE 3 Overview on the copy numbers per cell of HLA-A*02 and HLA-A*24TUMAPs HLA-A*02 TUMAPs were analyzed in eight samples, HLA-A*24 TUMAPsin six samples. nq = not quantified as peptide quantity was below LLOQQuantified Copies per cell in n (range of samples individual (% ofsamples and HLA- analyzed biological Allele Peptide code samples)replicates) A*02 IGF2BP3-001 1 (13%) 350-450 A*02 FAP-003 1 (13%)200-250 A*02 COL12A1-002 0 (0%) Nq A*02 MXRA5-001 1 (13%) 450 A*02NCAPG-001 1 (13%) 1000 A*02 COL6A3-002 0 (0%) Nq A*02 WNT5A-001 1 (13%)400 A*02 F2R-001 5 (63%)  50-300 A*02 HIF1A-001 3 (38%)  9000-30000 A*02MET-001 2 (25%) 200-250 A*02 CCNB1-002 0 (0%) Nq A*24 ASPM-002 0 (0%) NqA*24 SLC6A6-001 2 (33%) 1000-5000 A*24 MMP3-001 2 (33%) 100-250 A*24CDC2-001 0 (0%) Nq A*24 ASPM-001 0 (0%) Nq A*24 ATAD2-001 2 (33%)1500-6000 A*24 KIF2C-001 1 (17%) 3500 A*24 MET-006 3 (50%)  2500-13500A*24 AVL9-001 4 (67%)  1000-10000 A*24 PPAP2C-001 5 (83%)  200-1500 A*24UCHL5-001 1 (17%) 2500 A*24 UQCRB-001 1 (17%) 900

In order to visualize the LLOQ in the context of “peptide copies percell”, the “LLOQ per cell” was calculated for each TUMAP in each sampleusing the two formulas shown above. As the samples differ in the totalcell count, the LLOQ per cell is different for each sample (see FIG. 12and FIG. 13 for A*02 TUMAPs and FIG. 14 and FIG. 15 for A*24 TUMAPs).

Estimation of Error in Absolute TUMAP Quantitation

In order to estimate the variation in absolute TUMAP quantitation, theinventors considered the relative variation of the three majorexperimental results as described above:

a) the quantity of isolated TUMAP: relative deviation 1.8% (A*02) and2.1% (A*24)

b) the efficiency of TUMAP isolation: relative deviation 24% (A*02) and32% (A*24)

c) the cell count of the tissue sample: relative deviation 27%

Assuming normal distribution of the variable values, the relative error(G) of “copies per cell” may be calculated as the square root of the sumof the quadratic relative error of each variable:

$\sigma_{copies} = \sqrt{\left( \sigma_{{total}\mspace{14mu}{cellcount}} \right)^{2} + \left( \sigma_{{total}\mspace{14mu}{peptide}} \right)^{2} + \left( \sigma_{{isolation}\mspace{14mu}{efficiency}} \right)^{2}}$

With the values given above, the coefficient of variation for absolutepeptide copy numbers per cell is about 36% for HLA-A*02 peptides, and42% for HLA-A*24 peptides. To give an impression on the variation of theresults, the absolute and relative error of peptide copies per cell fora model peptide and sample was calculated (Table 4).

TABLE 4 Exemplary calculation of the absolute and relative error inabsolute TUMAP quantitation for a model peptide A*02 A*24 rel. errorabs. rel. error abs. value (%) error (%) error Total cell count/sample 1× 10⁸  27% —  27% — Total peptide [fmol] 16.25 1.8% — 2.1% — Efficiencyof peptideMHC 10%  24% —  32% — isolation Peptide copies per cell 1000 36% 360  42% 420

This model calculation suggests that for the complex multi-step analysisof absolute quantitation, the variation of results is still in anacceptable range. For individual TUMAPs, the relative error may deviatefrom the averaged error calculated here. TUMAP copy numbers per cell maybe quantitatively compared among different TUMAPs, allowing prioritizingTUMAPs to choose suitable antibody and/or soluble T cell receptortargets.

Comparison of the TUMAP Quantitation Method to Known Published Methods

An accurate approach for the absolute quantitation of MHC-associatedpeptide copy numbers per cell has not previously been shown. Mostimportantly, previously published methods for the quantitation ofMHC-bound peptides using MS analysis did not consider the loss ofantigen during sample preparation (Tan et al., 2011; Hogan et al.,2005). The group of Peter A. von Velen recently published a method forthe “accurate quantitation of MHC-bound peptides” (Hassan et al., 2014).In this technical note, an approach was used to quantify two minorhistocompatibility antigens, LB-NISCH-1A and LB-SSR1-1S, on EBV-LCLJYpp65 cells. However, the individual experimental steps differsubstantially, which is summarized in the table below:

TABLE 5 Comparison of the methods for TUMAPs quantitation of Hassan etal., and the present invention Hassan et al. present invention PeptideUsed only to determine the To determine the linear calibration linearrange, assuming all range, the LLOQ and curves peptides share the sameto quantify peptides; correlation of peptide quantity considers peptide-and MS signal (slope = 1) specific correlation of quantity and MS signalfor each individual peptide Peptide One point calibration: signalInternal standard method, quantitation ratio to spiked standard based onpeptide-specific peptide calibration curve, quantitation of samples nearthe LLOQ Efficiency of peptideMHC complexes spiked peptideMHC complexesisolation in lysate after 2 hour lysis and spiked directly after tissueclearance by centrifugation, homogenization, i.e. the disregards peptideloss in earliest point in peptide these steps isolation Samples Cellline Solid tumor tissue Sample Additional C18 Immediate usage of apreparation chromatography step prior to immunoprecipitated and thefinal nanoLC-MS/MS, used filtered sample for to reduce samplecomplexity. nanoLC-MS/MS Determination Counting of cells during cell DNAcontent analysis from of cell pellet preparation lysate of solid tissuesnumber Error Consider only variation of MS Variations in MS replicatescalculation replicates (CV 0.1-7.1%), but (CV on average 1.8-2.1%), notthe variation of peptideMHC isolation peptideMHC isolation (26%efficiency (CV on average and 91% respectively), and of 24-32%), andcell count the cell count. determination (CV on average 27%) areconsidered.

The copy numbers of the two peptides analyzed by Hassan et al. variedfrom 800 to 5300 (relative deviation 74%), and 3000 to 12000 (relativedeviation 60%) copies per cell among the biological replicates,respectively. The reason for this variation was not clearly discussed,but may be due to the usage of different MS instruments.

In summary, the more refined method of the present invention is expectedto contribute to more accurate and reliable results.

Quantification of Peptides Having Low Copy Numbers

In order to show the power of the inventive method, the data aspresented in the following table was generated. Peptides were identifiedthat are present in only very small copy numbers, amongst them peptidePDE11-001. It can be seen that the method allows the determination of asfew as about 10 copies of the peptide per cell.

TABLE 6 Quantification of peptides having low copy numbers PC—prostatecancer—Sequence PDE11-001 is ALLESRVNL (SEQ ID No. 25) Copies per cellNumber of samples Peptide Code Min Median Max >LLOQ >LOD evaluableSource/HLA Peptide 1 20 20 20 1 5 16 NSCLC/A*02 Peptide 2 10 30 300 1316 17 NSCLC/A*02 Peptide 3 10 30 50 4 10 18 NSCLC/A*02 Peptide 4 10 30100 17 17 19 NSCLC/A*02 Peptide 5 20 20 90 7 8 11 NSCLC/A*02 Peptide 610 20 50 6 6 10 NSCLC/A*02 Peptide 7 <10 30 200 9 12 15 PC/A*02PDE11-001 <10 10 30 8 9 10 PC/A*02

PDE11-001 is an HLA-A*02 binding peptide derived from phosphodiesterase11A (PDE11A), which catalyzes the hydrolysis of cAMP and cGMP, thusdownregulating the respective signalling pathways. Mutations in PDE11Ahave been associated with adrenocortical hyperplasia as well as withfamilial testicular germ cell tumors. The peptide was detected onprostate cancer samples, and also in hepatocellular, pancreatic andrenal cell carcinoma and not on any normal tissues.

REFERENCES AS CITED

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The invention claimed is:
 1. A method for quantification of at least oneMHC peptide ligand on a cell, comprising a) preparing a cell lysate fromcells presenting said at least one MHC peptide ligand from a biologicalsample comprising cells to obtain a preparation A, b) determining a cellcount of said preparation A, c) adding a pre-determined amount of saidat least one MHC peptide ligand labelled with a first isotope in an MHCcomplex to be quantified to said preparation A (“spiking I”) to obtain apreparation B, d) isolating the at least one MHC peptide ligand from thepreparation A and the at least one MHC peptide ligand labelled with afirst isotope from said preparation B to obtain a peptide eluate, e)adding a pre-determined amount of the at least one MHC peptide ligandlabelled with a second isotope to be quantified to said peptide eluate(“spiking II”) to obtain a preparation C, wherein the first isotope isdifferent from the second isotope, f) performing a mass spectrometryanalysis on said at least one MHC peptide ligand in the preparation C togenerate at least one fa) signal for said at least one MHC peptideligand labelled with the first isotope isolated from the preparation Bto calculate efficiency of said isolating, fb) signal for thepre-determined amount of said at least one MHC peptide ligand labelledwith the second isotope as added to the preparation C, and fc) signalfor said at least one MHC peptide ligand from said preparation A, f1)performing a mass spectrometry analysis on serially titrated amounts ofsaid at least one MHC peptide ligand labelled with a third isotope andthe pre-determined amount of said at least one MHC peptide ligandlabelled with a fourth isotope as an internal standard to generate f1a)signal for the serially titrated amounts of said at least one MHCpeptide ligand labelled with a third isotope, and f1b) signal for thepre-determined amount of said at least one MHC peptide ligand labelledwith a fourth isotope, wherein the third isotope is different from thefourth isotope, f2) plotting a ratio of the signal of f1a)/the signal off1b) to generate a calibration curve, wherein a lower limit ofquantitation (LLOQ) is determined when the ratio of the signal off1a)/the signal of f1b) deviates from linearity in the calibrationcurve, and; g) quantifying said at least one MHC peptide ligand in thepreparation A based on a comparison of the signals as obtained in f)with ga) the cell count as obtained, gb) the pre-determined amount ofsaid at least one peptide-MHC ligand labelled with the first isotopeand/or peptide-MHC ligand complex labelled with the first isotope to bequantified as added to the preparation B, and gc) the pre-determinedamount of at least one MHC peptide ligand labelled with a second isotopeto be quantified as added to the preparation C, wherein the quantifyingin g) comprises selecting a ratio of the signal of fc)/the signal of fb)at or above the LLOQ and calculating the copy number of the at least oneMHC peptide ligand per cell based on the selected ratio in thecalibration curve.
 2. The method according to claim 1, wherein said atleast one MHC peptide ligand is selected from a tumor associated peptide(TAA) or disease associated peptide (DAA).
 3. The method according toclaim 1, wherein said biological sample comprising cells is selectedfrom a tissue sample, a blood sample, a tumor sample, or a sample of aninfected tissue.
 4. The method according to claim 1, wherein thepreparing cells comprises enzymatic digestion of tissues, and/orcellular lysis.
 5. The method according to claim 1, wherein said cellcount is determined using a method selected from counting cell nuclei,photometric DNA-determination, fluorimetric DNA-determination, orquantitative PCR.
 6. The method according to claim 1, further comprisingdetermining the amount of at least one type of HLA-molecule in saidpreparation A.
 7. The method according to claim 1, wherein the isolatingcomprises using chromatography.
 8. The method according to claim 1,further comprising selecting overpresented, overexpressed and/ortumor-specific MHC peptide ligands for analysis.
 9. The method accordingto claim 1, wherein said method is capable of being performed and/or isperformed on a high-throughput basis.
 10. The method according to claim1, wherein said method consists of said a) to g).
 11. The methodaccording to claim 1, wherein said biological sample is derived from oneindividual, or from a group of individuals suffering from the samemedical condition.
 12. The method according to claim 11, furthercomprising generating a personalized MHC ligand profile or apersonalized disease-specific MHC ligand profile, based on said MHCpeptide ligands as quantified.
 13. The method according to claim 1,wherein the isolating comprises using affinity chromatography.
 14. Themethod according to claim 1, wherein said biological sample is derivedfrom one individual.
 15. The method according to claim 11, furthercomprising generating a personalized MHC ligand profile based on saidMHC peptide ligands as quantified.
 16. The method according to claim 11,further comprising generating a personalized disease-specific MHC ligandprofile based on said MHC peptide ligands as quantified.